Retrospective on a decade of machine learning for chemical discovery.
Where this comes from
- Record sourced from PubMed, PMID 32994393.
- Also identified by DOI 10.1038/s41467-020-18556-9 and PMC identifier 7525448.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific achievements of machine learning models in the field of computational chemistry by considering selected studies of electronic structure, interatomic potentials, and chemical compound space in chronological order.